Internship Computer Vision & Machine Learning Research - LLM Efficiency

Apple Inc.; Zürich; Vor Ort; CHF 42.000 - 51.000; Teilzeit

Zusammenfassung

Apple Inc. in Zürich is seeking a research intern for an Internship in Computer Vision & ML focused on LLM efficiency. You will join world-class researchers to advance frontier models, diffusion models, and on-device ML through code prototyping, large-scale experiments, and writing up results for submission.

The role suits a PhD candidate with publications, strong Python and multi-language software engineering skills, and a passion for rigorous ML research in a collaborative environment.

Qualifikationen

• Working towards a doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent.
• 6 months dedication is preferred, and starting no later than March 2026
• Proven research expertise in machine learning.
• Publication record in relevant conferences (e.g., NeurIPS, ICLR, ICML, COLM, etc).
• Solid software engineering skills in complex, multi-language systems. Fluency in Python.

Aufgaben

• Identify promising research opportunities and review state-of-the-art methods and literature.
• Craft novel approaches and implement them as code prototypes.
• Plan and run large-scale experiments across multi-node, multi-GPU systems.
• Write a paper and see it through to submission.

Kenntnisse

Python

ML research

Publications

Software engineering

Ausbildung

PhD in CS/Engineering/Data Science

Tools

PyTorch

TensorFlow

Jobbeschreibung

Internship Computer Vision & Machine Learning Research - LLM Efficiency

We're seeking research interns to create breakthrough innovations in machine learning. We are particularly interested in efficiency of frontier models, including LLMs and diffusion models. You will work in an organization of world-class machine learning researchers and engineers. Our work powers cutting-edge technologies across the Apple ecosystem and is published in the most selective scientific journals and conferences.

Description

You are in your final years of a PhD programme in Machine Learning and have already published some of your work at top-tier venues in the field. During your time with us, you will continue sharpening your research skills as we go through the various collaborative stages of an ML research project: Identifying a promising research opportunity, reviewing state-of-the-art methods and relevant literature, crafting novel approaches, implementing them as code prototypes, planning and running large-scale experiments across multi-node, multi-GPU systems, writing a paper, and seeing it through to submission.Topics of interest include but are not limited to frontier models, efficiency of LLM inference and training, on-device models, speculative decoding, contextual sparsity, quantization and compression. We are a team of best-in-the-world research scientists and engineers with deep experience in computer vision, machine learning, robotics, computer graphics, and related areas. We work on exciting new technologies that bring joy to millions of people.In our daily work, the team stays innovative, productive, and fun by sharing some key values:- Passion for the mission: We're here to make something extraordinary. We seek whatever work is right and strive for the best possible results.- Modesty: The right answer is more significant than being right. We search for solutions as a team and value clear-eyed feedback.- Lean habits: You can't grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions.

Minimum Qualifications

• You are working towards a doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent.
• 6 months dedication is preferred, and starting no later than March 2026
• Proven research expertise in machine learning.
• Publication record in relevant conferences (e.g., NeurIPS, ICLR, ICML, COLM, etc).
• Solid software engineering skills in complex, multi-language systems. Fluency in Python.

Preferred Qualifications

• Expertise in ML algorithms and top practices for working with deep learning systems
• Proficiency with ML modeling frameworks (PyTorch, Tensorflow, etc.)

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.

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